"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE__:List[str]									=			{
    """configuration_electra""": ["""ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ElectraConfig""", """ElectraOnnxConfig"""],
    """tokenization_electra""": ["""ElectraTokenizer"""],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE__:Union[str, Any]									=			["""ElectraTokenizerFast"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE__:Any									=			[
       """ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """ElectraForCausalLM""",
       """ElectraForMaskedLM""",
       """ElectraForMultipleChoice""",
       """ElectraForPreTraining""",
       """ElectraForQuestionAnswering""",
       """ElectraForSequenceClassification""",
       """ElectraForTokenClassification""",
       """ElectraModel""",
       """ElectraPreTrainedModel""",
       """load_tf_weights_in_electra""",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE__:int									=			[
       """TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """TFElectraForMaskedLM""",
       """TFElectraForMultipleChoice""",
       """TFElectraForPreTraining""",
       """TFElectraForQuestionAnswering""",
       """TFElectraForSequenceClassification""",
       """TFElectraForTokenClassification""",
       """TFElectraModel""",
       """TFElectraPreTrainedModel""",
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE__:List[str]									=			[
       """FlaxElectraForCausalLM""",
       """FlaxElectraForMaskedLM""",
       """FlaxElectraForMultipleChoice""",
       """FlaxElectraForPreTraining""",
       """FlaxElectraForQuestionAnswering""",
       """FlaxElectraForSequenceClassification""",
       """FlaxElectraForTokenClassification""",
       """FlaxElectraModel""",
       """FlaxElectraPreTrainedModel""",
   ]


if TYPE_CHECKING:
   from .configuration_electra import ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP, ElectraConfig, ElectraOnnxConfig
   from .tokenization_electra import ElectraTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_electra_fast import ElectraTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_electra import (
          ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
          ElectraForCausalLM,
          ElectraForMaskedLM,
          ElectraForMultipleChoice,
          ElectraForPreTraining,
          ElectraForQuestionAnswering,
          ElectraForSequenceClassification,
          ElectraForTokenClassification,
          ElectraModel,
          ElectraPreTrainedModel,
          load_tf_weights_in_electra,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_electra import (
          TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFElectraForMaskedLM,
          TFElectraForMultipleChoice,
          TFElectraForPreTraining,
          TFElectraForQuestionAnswering,
          TFElectraForSequenceClassification,
          TFElectraForTokenClassification,
          TFElectraModel,
          TFElectraPreTrainedModel,
      )

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_electra import (
          FlaxElectraForCausalLM,
          FlaxElectraForMaskedLM,
          FlaxElectraForMultipleChoice,
          FlaxElectraForPreTraining,
          FlaxElectraForQuestionAnswering,
          FlaxElectraForSequenceClassification,
          FlaxElectraForTokenClassification,
          FlaxElectraModel,
          FlaxElectraPreTrainedModel,
      )

else:
   import sys

   SCREAMING_SNAKE_CASE__:str									=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

"""simple docstring"""


import fire

from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer





def      lowerCamelCase_					(   __lowerCAmelCase  ,       __lowerCAmelCase  ,       **__lowerCAmelCase							)				->   List[str]:




						'''simple docstring'''



						lowerCamelCase__   =AutoConfig.from_pretrained(__lowerCAmelCase  ,       **__lowerCAmelCase							)
						lowerCamelCase__   =AutoModelForSeqaSeqLM.from_config(__lowerCAmelCase							)
						model.save_pretrained(__lowerCAmelCase							)
						AutoTokenizer.from_pretrained(__lowerCAmelCase							).save_pretrained(__lowerCAmelCase							)
						return model


if __name__ == "__main__":
	fire.Fire(save_randomly_initialized_version)


